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Machine Learning Foundations: A Case Study Approach(으)로 돌아가기

워싱턴 대학교의 Machine Learning Foundations: A Case Study Approach 학습자 리뷰 및 피드백

4.6
별점
11,692개의 평가
2,801개의 리뷰

강좌 소개

Do you have data and wonder what it can tell you? Do you need a deeper understanding of the core ways in which machine learning can improve your business? Do you want to be able to converse with specialists about anything from regression and classification to deep learning and recommender systems? In this course, you will get hands-on experience with machine learning from a series of practical case-studies. At the end of the first course you will have studied how to predict house prices based on house-level features, analyze sentiment from user reviews, retrieve documents of interest, recommend products, and search for images. Through hands-on practice with these use cases, you will be able to apply machine learning methods in a wide range of domains. This first course treats the machine learning method as a black box. Using this abstraction, you will focus on understanding tasks of interest, matching these tasks to machine learning tools, and assessing the quality of the output. In subsequent courses, you will delve into the components of this black box by examining models and algorithms. Together, these pieces form the machine learning pipeline, which you will use in developing intelligent applications. Learning Outcomes: By the end of this course, you will be able to: -Identify potential applications of machine learning in practice. -Describe the core differences in analyses enabled by regression, classification, and clustering. -Select the appropriate machine learning task for a potential application. -Apply regression, classification, clustering, retrieval, recommender systems, and deep learning. -Represent your data as features to serve as input to machine learning models. -Assess the model quality in terms of relevant error metrics for each task. -Utilize a dataset to fit a model to analyze new data. -Build an end-to-end application that uses machine learning at its core. -Implement these techniques in Python....

최상위 리뷰

BL

Oct 17, 2016

Very good overview of ML. The GraphLab api wasn't that bad, and also it was very wise of the instructors to allow the use of other ML packages. Overall i enjoyed it very much and also leaned very much

SZ

Dec 20, 2016

Great course!\n\nEmily and Carlos teach this class in a very interest way. They try to let student understand machine learning by some case study. That worked well on me. I like this course very much.

필터링 기준:

Machine Learning Foundations: A Case Study Approach의 2,717개 리뷰 중 2626~2650

교육 기관: Rajiv K

Jun 20, 2020

Have to improve for other environment.

have to explain other alternative too.

교육 기관: Vamshi S G

Jun 28, 2020

i think the course should be updated, graphlab and some other are outdated.

교육 기관: Julien F

Nov 17, 2017

Some quiz questions were vague and/or ambiguous, or not covered in talks.

교육 기관: Marco M

Dec 04, 2015

Too much synthetic on very important parts, too much focused on graphlab

교육 기관: Pawan K S

May 15, 2016

Nice introductory course but too much dependence on graphLab create

교육 기관: Jesse W

Dec 24, 2016

It is better if allow me upgrade only when I finished this course.

교육 기관: Tushar k

Dec 01, 2015

Good course to begin machine learning with but it's too easy !!

교육 기관: Konstantinos L

Jan 08, 2018

Nice course but too easy. Assignments should be more difficult

교육 기관: Atharv J

Sep 14, 2020

The course should be taught in pandas rather than graphlab.

교육 기관: Max F

Jan 10, 2016

Not a bad course, but extremely basic. Was expecting more.

교육 기관: Adrien L

Feb 02, 2017

No good without the missing course and capstone projects

교육 기관: Himanshu S R

Apr 16, 2020

It uses turicreate which is not available for windows .

교육 기관: Aleksey C

Dec 11, 2016

....mmm fsdfg gsgsd sgsdgsdg sdsdgsdg ggsgsd sgdsdgsg

교육 기관: HITESH D

Jun 15, 2020

Installing software parts gave me a very hard time.

교육 기관: Bastian M P

Jun 01, 2016

Could go a little more in detail on the algorithms.

교육 기관: Jaime O

Jan 31, 2017

The Deep Learning part needs to be improved

교육 기관: Chen S

Oct 26, 2015

Very basic, the quizzes aren't clear enough

교육 기관: Harsh V K

May 08, 2019

Should use Python 3 instead of Python 2

교육 기관: Jorge A C C

May 29, 2016

It is a very simple course.

교육 기관: RAGHUPATHI R R

Jun 25, 2020

Good for knowledge

교육 기관: Fredick A S

Apr 07, 2018

No python..

교육 기관: Nasimul J F

Aug 16, 2020

THANK YOU.

교육 기관: Kai C

Nov 25, 2015

Too easy

교육 기관: JONNALAGADDA A

Sep 12, 2020

good

교육 기관: sakthivel

Sep 05, 2020

Good